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叶小敏,林明森,宋清涛,廖菲,梁超,周旋.复合雷达后向散射模型与合成孔径雷达、散射计和高度计海面雷达后向散射观测的比较分析[J].海洋学报,2019,41(7):123-135
复合雷达后向散射模型与合成孔径雷达、散射计和高度计海面雷达后向散射观测的比较分析
Comparisons of composite radar backscattering model and sea surface radar backscatter from synthetic aperture radar, scatterometer and altimeter
投稿时间:2017-04-24  修订日期:2018-04-26
DOI:10.3969/j.issn.0253-4193.2019.07.011
中文关键词:  雷达后向散射模型  合成孔径雷达  散射计  高度计
英文关键词:radar backscattering model  synthetic aperture radar  scatterometer  altimeter
基金项目:国家自然科学基金(41876211,41506206,41876204,41476152,41276019);广东省省级科技计划项目(2013B020200013);国家重点研发计划(2016YFC1401000);国家自然科学基金委员会-山东省人民政府联合资助海洋科学研究中心项目(U1406404)。
作者单位E-mail
叶小敏 国家卫星海洋应用中心, 北京 100081
国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081 
 
林明森 国家卫星海洋应用中心, 北京 100081
国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081
青岛海洋科学与技术试点国家实验室 区域海洋动力学与数值模拟功能实验室, 山东 青岛 266237 
 
宋清涛 国家卫星海洋应用中心, 北京 100081
国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081 
qsong@mail.nsoas.org.cn 
廖菲 广州市气象台, 广东 广州 511430  
梁超 国家卫星海洋应用中心, 北京 100081
国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081 
 
周旋 北京5111信箱, 北京 100094  
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中文摘要:
      海洋微波散射模型相比于以经验统计建立的地球物理模式函数具有不受特定微波频率限制的优势。组合布拉格散射模型和几何光学模型形成了复合雷达后向散射模型。利用南海北部气象浮标2014年海面风速风向实测值作为散射模型输入,分别比较了复合雷达后向散射模型与RADARSAT-2卫星C波段SAR、HY-2A卫星Ku波段微波散射计的海面后向散射系数,偏差分别为(-0.22±1.88) dB (SAR)、(0.33±2.71) dB (散射计VV极化)和(-1.35±2.88) dB (散射计HH极化);以美国浮标数据中心(NDBC)浮标2011年10月1日至2014年9月30日共3年的海面风速、风向实测值作为散射模型输入,分别比较了复合雷达后向散射模型与Jason-2、HY-2A卫星Ku波段高度计海面后向散射系数,偏差分别为(1.01±1.15) dB和(1.12±1.29) dB。中等入射角和垂直入射下的卫星传感器后向散射系数观测值与复合雷达后向散射模型模拟值比较,具有不同的偏差,但具有相同的海面风速检验精度,均方根误差小于1.71 m/s。结果表明,复合雷达后向散射模型可模拟计算星载SAR、散射计和高度计观测条件下的海面雷达后向散射系数,且与CMOD5、NSCAT-2、高度计业务化海面风速反演的地球物理模式函数的计算结果具有一致性;复合雷达后向散射模型可用于微波遥感器的定标与检验、海面雷达后向散射的模拟。
英文摘要:
      Comparison with Geophysical Model Function (GMF) developed by methods of empirical statistics, ocean microwave scattering model works well at all microwave frequency. Composite radar backscattering model is comprised of Bragg scattering model and geometrical optics model. We calculated the normalized radar cross sections (NRCSs) from the composite scattering model by using the sea surface wind speeds and directions measured by buoys moored in the northern of South China Sea in the whole year of 2014, and then compared them with SAR on board RADARSAT-2 at C-band, microwave scatterometer on board HY-2A satellite (HSCAT) at Ku-band, respectively. The biases of comparison are (-0.22±1.88) dB (for SAR), (0.33±2.71) dB (for HSCAT in VV polarization) and (-1.35±2.88) dB (for HSCAT in HH polarization), respectively. We also calculated the NRCSs from the model by using the sea surface wind speeds and directions measured by NDBC buoys in the time period from October 1, 2011 to September 30, 2014, and then compared them with radar altimeter on board Jason-2 and HY-2A both at Ku-band with the bias of (1.01±1.15) dB and (1.12±1.29) dB, respectively. Although the biases of NRCSs between space-borne sensors and composite scattering model in medium and normal incidence are different each other, the accuracies of their sea surface wind speed products are the same(i.e. the root mean square errors are all less than 1.71 m/s). The results show that we can simulate the sea surface radar NRCSs of satellite-borne SAR, microwave scatterometer, and altimeter by using the composite radar backscattering model, and the simulations are consistent with that of CMOD5, NSCAT-2 and the GMF of operational wind retrieval for altimeter. It also indicates that the composite radar backscattering model could be used in calibration and validation of microwave sensors and simulation of radar backscatter from sea surface.
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